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Maximum Entropy Distribution Function and Uncertainty Evaluation Criteria
Authors:Chen  Bai-yu  Kou  Yi  Zhao  Daniel  Wu  Fang  Wang  Li-ping  Liu  Gui-lin
Institution:1.College of Engineering, University of California Berkeley, Berkeley, 94720, USA
;2.Dornsife College, University of Southern California, Los Angeles, 90007, USA
;3.Department of Mathematics, Harvard University, Cambridge, 02138, USA
;4.Statistics and applied probability, University of California Santa Babara, Santa Babara, 93106, USA
;5.School of Mathematical Sciences, Ocean University of China, Qingdao, 266100, China
;6.College of Engineering, Ocean University of China, Qingdao, 266100, China
;
Abstract:Marine environmental design parameter extrapolation has important applications in marine engineering and coastal disaster prevention. The distribution models used for environmental design parameter usually pass the hypothesis tests in statistical analysis, but the calculation results of different distribution models often vary largely. In this paper,based on the information entropy, the overall uncertainty test criteria were studied for commonly used distributions including Gumbel, Weibull, and Pearson-III distribution. An improved method for parameter estimation of the maximum entropy distribution model is proposed on the basis of moment estimation. The study in this paper shows that the number of sample data and the degree of dispersion are proportional to the information entropy, and the overall uncertainty of the maximum entropy distribution model is minimal compared with other models.
Keywords:
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